However, as is often the case, the story shouldn’t be so black and white. In the coming years, AI-based chatbot technology will evolve to meet lofty expectations and drive business value.

Rules-Based vs. AI-Driven Chatbots

The fastest, easiest way to deploy a chatbot is to settle for a decision tree model. You configure the bot to follow a specific, linear interaction that walks users through a list of decisions to reach the desired endpoint.

These rules-based chatbots are effective on the front lines of your customer support department because they can help keep trivial issues away from human agents. However, rules-based chatbots do nothing to capitalize on the hype surrounding this technology.

Rules-based chatbots are inflexible, only capable of executing pre-defined processes. To meet the lofty expectations of this technology, we need AI-driven chatbots.

And therein lies the problem. While people are focused on the failure of some chatbots, the real challenge isn’t with the medium—it’s with the advancement of artificial intelligence engines underneath.

Two Keys to the Evolution of AI-Driven Chatbots

Early chatbot adopters expected too much, too quickly from the technology. In many cases, brands were pushing the limits of AI-driven chatbots and hurting customer experiences in the process.

However, that doesn’t mean chatbots don’t have value today. You just have to deploy them within the limits of what rules-based models and current AI engines allow.

In the next few years, there are two key evolutions of chatbot technology that will help brands unlock the value that drove hype in 2016.

1. Improvement of Natural Language Processing

When chatbots gained favor in 2016, it was on the back of consumers trending away from mobile apps and toward messaging services. In an effort to meet customers where they spent so much time, brands wanted to build conversations with chatbots.

Except you can’t build a real conversation with a rules-based chatbot. Even a quality rules-based chatbot will still feel robotic and unnatural.

Making the most of a conversational interface like messaging requires a conversational chatbot. That means building an AI-driven chatbot with natural language processing (NLP) at the core.

The only problem is that NLP hasn’t advanced enough to create truly conversational experiences. If you’ve ever asked Siri a question and the words register, but you either can’t get a response or get the wrong response, you know what this is like in the real world.

In the next few years, we’ll start to see NLP developers get closer to mimicking the circular nature of human conversations. Once machines have the language processing power as well as the ability to capture user intent, we’ll see the next level of chatbot use cases.

2. Moving Away from Platforms and Lock-in

The whole point of embracing chatbot technology is to meet customers where they want to interact. As consumers stopped downloading as many apps, brands wanted to shift to WhatsApp, WeChat, and Facebook Messenger to keep up with attention.

However, the goal shouldn’t be to follow whichever platform is most popular and set up a chatbot there. Instead, we need AI-driven chatbots that are platform agnostic.

The reality is that consumers make purchase decisions across so many different channels. They bounce from mobile to desktop to in-person shopping and back again, sometimes up to 10 times for a single decision. While you may have been able to specialize in certain platforms in the past, you have to be accessible anywhere and at any time now.

That’s why the next AI-driven chatbots will be platform agnostic and come loaded with countless integrations. You don’t want to build your chatbot directly on Facebook Messenger—you want a chatbot that spans many channels, including Facebook Messenger.

It’s a subtle distinction, but an important one for the success of your chatbot for customer engagement.

Chatbots Are One Piece of a Larger CX Strategy

It’s great to get a head start with chatbots today so you can meet the high expectations of customers engagement. And as AI-driven chatbot technology improves, you’ll have a head start to build upon.

However, it’s important to remember that chatbots alone do not complete a customer experience strategy. Rather, they’re one piece of a larger puzzle that will help you engage with customers anywhere, anytime, and at any point in the buyer’s journey.

The real key is finding a way to properly integrate chatbots into your other CX tactics and processes. And sometimes, that’s easier said than done.

Technology that drives truly conversational AI-based chatbots is closer than we might think. Companies are already finding ways to create more natural chatbot experiences that fit into overarching CX strategies.

If you want to learn more about this technology, take a look at what the team at Cognigy is doing. Find out how their AI engine can power the next generation of customer experiences.